Literature DB >> 7670862

Assessment of developmental toxicity potential of chemicals by quantitative structure-toxicity relationship models.

V K Gombar1, K Enslein, B W Blake.   

Abstract

Statistically significant quantitative structure-toxicity relationship (QSTR) models have been developed for assessing developmental toxicity potential (DTP) of chemicals. Three submodels, one each for aliphatic, heteroaromatic and carboaromatic compounds, have been cross-validated to ascertain their robustness. The specificities of the models range from 86% to 97%, and their sensitivities between 86% and 89%. For convenient computer-assisted application, the models are installed in a toxicity assessment software package, TOPKAT, which has been recently enhanced with algorithms to identify whether or not a query structure is inside the optimum prediction space (OPS) of a QSTR model. Different functionalities of the TOPKAT program have been explained by assessing the DTP of a number of compounds not used in the model training sets. The DTP of 18 existing drugs was assessed using these models; the DT assay results were available for 5 of these. Three of these 5 molecules were identified to be inside the OPS and their TOPKAT assessment matched their experimental assignment.

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Year:  1995        PMID: 7670862     DOI: 10.1016/0045-6535(95)00119-s

Source DB:  PubMed          Journal:  Chemosphere        ISSN: 0045-6535            Impact factor:   7.086


  3 in total

Review 1.  Joint toxicity of alkoxyethanol mixtures: contribution of in silico applications.

Authors:  H R Pohl; P Ruiz; F Scinicariello; M M Mumtaz
Journal:  Regul Toxicol Pharmacol       Date:  2012-06-28       Impact factor: 3.271

2.  CAESAR models for developmental toxicity.

Authors:  Antonio Cassano; Alberto Manganaro; Todd Martin; Douglas Young; Nadège Piclin; Marco Pintore; Davide Bigoni; Emilio Benfenati
Journal:  Chem Cent J       Date:  2010-07-29       Impact factor: 4.215

3.  A Toxicity Prediction Tool for Potential Agonist/Antagonist Activities in Molecular Initiating Events Based on Chemical Structures.

Authors:  Kota Kurosaki; Raymond Wu; Yoshihiro Uesawa
Journal:  Int J Mol Sci       Date:  2020-10-23       Impact factor: 5.923

  3 in total

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